#1 Processing steps
- Perform the simulation
For each flight simulation, “Flightapp” generates 3 tables:
- flight (position, speed, etc.)
- actions (control actions performed by the pilot)
- imquery (information checks performed by the pilot)
- Discretize simulation tables
- For each flight, “PostFlight” generates 1 table (ending with “dis”),
and we export as CSV for processing with R.
- All CSV flights need to be stored in a specific folder of the R path
(“csv_in/”).
- Create “big” dataset in R
Using the function “createInfoDF”, that returns a list of dataframes, we
obtain the dataset with all flights and the initial variables. Useless
rows are discarded in this step.
- The “flights_info” table
We also obtain a dataframe with a summary of the dataset, we call it
“flights_info”:
| 1 |
20220121223209dis |
1977 |
1 |
1930 |
0.0004094 |
0.3090253 |
0.0000000 |
0.9809517 |
0.3187659 |
| 2 |
20220121230742dis |
1949 |
1 |
1917 |
0.0002194 |
0.0529804 |
0.8868023 |
1.0245125 |
0.2287594 |
| 3 |
20220123194045dis |
1996 |
1 |
1917 |
0.0004871 |
0.2986273 |
0.0000000 |
0.6667019 |
0.1708445 |
| 4 |
20220125113713dis |
1962 |
1 |
1919 |
0.0005534 |
0.1627686 |
0.0000000 |
0.6390038 |
0.1720996 |
| 5 |
20220316145030dis |
1943 |
1 |
1845 |
0.0003181 |
0.0552582 |
3.1978320 |
1.1774307 |
0.2293945 |
| 6 |
20220316153735dis |
1900 |
1 |
1871 |
0.0003222 |
0.0161252 |
0.0000000 |
0.7176776 |
0.1638964 |
| 7 |
20220512161006dis |
1962 |
1 |
1920 |
0.0005859 |
0.3391114 |
0.0000000 |
0.8794430 |
0.2712950 |
| 8 |
20220523212158dis |
1911 |
1 |
1890 |
0.0003100 |
0.0162455 |
0.0000000 |
0.8161311 |
0.1295424 |
| 9 |
20220524203226dis |
1938 |
1 |
1904 |
0.0003080 |
0.0277673 |
0.0000000 |
0.7762082 |
0.1418865 |
| 10 |
20220527110631dis |
1934 |
1 |
1896 |
0.0004087 |
0.1945740 |
0.0000000 |
0.5697111 |
0.1893888 |
| 11 |
20220528112722dis |
1917 |
1 |
1888 |
0.0004087 |
0.0203251 |
1.9597458 |
1.0638933 |
0.1926771 |
| 12 |
20220529142028dis |
1905 |
1 |
1877 |
0.0003161 |
0.0143047 |
0.0000000 |
0.7765556 |
0.1639485 |
| 13 |
20220530144122dis |
1880 |
1 |
1860 |
0.0004797 |
0.0182252 |
0.0000000 |
0.8486337 |
0.1627407 |
| 14 |
20220531151247dis |
1907 |
1 |
1884 |
0.0003127 |
0.0318930 |
0.0000000 |
0.8364559 |
0.1990694 |
| 15 |
20220601154130dis |
1916 |
1 |
1889 |
0.0002255 |
0.1581891 |
0.0000000 |
0.5939349 |
0.1251029 |
| 16 |
20220602160225dis |
1948 |
1 |
1887 |
0.0003107 |
0.0383346 |
0.0000000 |
0.5766042 |
0.1002377 |
| 17 |
20220603192433dis |
1914 |
1 |
1877 |
0.0004804 |
0.0215958 |
0.0000000 |
0.5849015 |
0.1181386 |
| 18 |
20220604200536dis |
1923 |
1 |
1893 |
0.0003925 |
0.1224819 |
0.0000000 |
0.4652699 |
0.0828084 |
| 19 |
20220906134140dis |
1914 |
1 |
1882 |
0.0003134 |
0.0731759 |
0.0000000 |
0.9665278 |
0.1924313 |
| 20 |
20220906153443dis |
1894 |
1 |
1872 |
0.0004932 |
0.1074852 |
0.0000000 |
0.8681653 |
0.1823608 |
| 21 |
20220906200133dis |
1916 |
1 |
1874 |
0.0003201 |
0.1345631 |
0.0000000 |
0.9313942 |
0.1819750 |
| 22 |
20220907072201dis |
1927 |
1 |
1898 |
0.0002248 |
0.0846236 |
0.0000000 |
0.5042391 |
0.1283485 |
| 23 |
20230617165137dis |
1917 |
1 |
1886 |
0.0108562 |
0.0359365 |
17.9215270 |
2.0249735 |
0.5695217 |
| 24 |
20230909190522dis |
1862 |
1 |
1845 |
0.0003634 |
0.0701776 |
8.1300813 |
2.0921676 |
0.4119222 |
| 25 |
20230909184627dis |
1856 |
1 |
1815 |
0.0005068 |
0.0271638 |
0.0000000 |
0.7527038 |
0.1525801 |
| 26 |
20240208215046dis |
1878 |
1 |
1846 |
0.0005169 |
0.1112870 |
0.0000000 |
0.7122132 |
0.1827100 |
| 27 |
20240208211725dis |
1870 |
1 |
1812 |
0.0002640 |
0.2999301 |
0.0000000 |
0.6387079 |
0.1753212 |
- For each one of the 27 flights, we see the total number of rows and
the rows of interest (initialRows, firstIndex, lastIndex), which are
kept.
- We also obtain basic statistics of the deviation:
- deviationfirstIndex & deviationlastIndex provide an indication
that the flight is acceptable at the beginning and the end.
- deviationexceeded is the percentage of samples where the deviation
is bigger than 1NM.
- deviationmax is the maximum deviation within the flight, and
deviationmean is the mean.
- Overview of the flights
This is a map representation of each flight: